MT-15.02

Title:

Author(s):

Marzieh Golbaz

Oral Defence Date:

Wednesday, May 13, 2015 - 17:00

Location:

TH 434

Committee:

Committee: Profs. Dragutin Petkovic, Ilmi Yoon and Kaz Okada

Abstract:

Early and accurate assessment of severity of viral respiratory infections (VRIs) is important for improved survival and reduced mortality and morbidity in infants. This study proposes a novel imaging biomarker framework with chest x-ray images to assess the severity of pediatric VRIs. Having the manually segmented lung fields, the large unwanted objects are removed using a graph cut-based segmentation with asymmetry constraint. Each lung field is then subdivided into quadruple areas, allowing the severity of each area to be quantified using information-theoretic heterogeneity measures. The experimental results with a dataset of 148 images and the ground truth severity scores provided by a board-certified pediatric pulmonologist, demonstrates the efficiency and usefulness of the proposed method as a non-invasive imaging biomarker to diagnose and locate lung infections.